The Internet has become increasingly popular with end users, to the extent that advertisers are recently attracted to this medium for purchasing advertising space. Accordingly, online advertising is an important piece of the marketing campaigns and sales strategies of many client businesses, advertisers, or content providers. In order to accommodate advertisers wishing to post online advertisements, web pages are often designed to offer content regions therein for sale. These content regions are configured to present advertisements to the end user upon navigating to the web pages. However, these advertisements are presented only if the advertisers place orders to purchase a particular number of display instances, or impressions. Typically, a delivery engine is responsible for accepting the orders and distributing the advertisements for presentation at the content regions of selected web pages.
Typically, when orders are placed to the delivery engine, they are guaranteed upon accepting the order. That is, the delivery engine has made a commitment to show the number of impressions as instructed in the orders. For instance, if an advertiser orders one million impressions of a particular advisement, there automatically exists an agreement that the delivery engine will cause each of the one million impressions to occur. If the delivery engine does not meet its obligation to present each of the one million impressions of the advertisement, or underdelivers, the advertisers may experience customer dissatisfaction which may result in the delivery engine losing business or being forced to offer rebates to retain their current business. This problem of fulfilling the orders accepted by the delivery engine is exaggerated in the situation where the delivery engine is servicing multitudes of advertisers that each place various orders with different time frames for presenting impressions of the advertisements being ordered.
Conventional mechanisms for ascertaining how to deliver ordered impressions of advertisements and for determining whether inventory is available for accepting new orders are labor-intensive (e.g., requiring a considerable amount of user-initiated tracking and calculations) and are not fluid, flexible, or efficient. Further, these conventional mechanisms are ad-hoc solutions that cannot dynamically react to a change in orders or inventory. As such, employing a sequence of linear programs that dynamically identify optimal allocations of the available inventory, and that facilitate deciding whether to accept a new order by evaluating currently accepted orders along with the new order against available inventory, would enhance the advertiser's experience when conducting a marketing campaign via the delivery engine.